Skip to main content
SpringerLink
Log in

Task Oriented Control of a Humanoid Robot Through the Implementation of a Cognitive Architecture

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This work presents a novel approach on task oriented control of a humanoid robot through the implementation of a cognitive architecture. The architecture developed here provides humanoid robots with systems that allow them to continuously learn new skills, adapt these skills to new contexts and robustly reproduce new behaviours in dynamical environments. This architecture can be thought of as a first stepping stone upon which to incrementally build more complex cognitive processes, providing this way a minimum degree of intelligence for the humanoid robot. Several experiments are conducted to prove the validity of the system and to test the operation of the architecture.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Albus, J.: Outline for a theory of intelligence. IEEE Trans. Syst. Man Cybern. 21(3), 473 –509 (1991). doi:10.1109/21.97471

    Article  MathSciNet  Google Scholar 

  2. Albus, J.S.: The nist real-time control system (rcs): an approach to intelligent systems research. J. Exp. Theor. Artif. Intell. 9(2-3), 157–174 (1997)

    Article  Google Scholar 

  3. Albus, J.S., Barbera, A.J.: RCS: A cognitive architecture for intelligent multi-agent systems. Ann. Rev. Control 29(1), 87–99 (2005)

    Article  Google Scholar 

  4. Anderson, J.R., Bothell, D., Byrne, M.D., Douglass, S., Lebiere, C., Qin, Y.: An integrated theory of the mind. Psychol. Rev. 111, 1036–1060 (2004)

    Article  Google Scholar 

  5. Bechtel, W.: Representations and cognitive explanations: Assessing the dynamicist’s challenge in cognitive science. Cognit. Sci. 22(3), 295–318 (1998)

    Article  Google Scholar 

  6. Billard, A., Calinon, S., Dillmann, R., Schaal, S.: Robot programming by demonstration. In: Siciliano, B., Khatib, O. (eds.) Handbook of Robotics, pp 1371–1394. Springer, Secaucus, NJ, USA (2008)

  7. Brooks, R., Breazeal, C., Marjanović, M., Scassellati, B., Williamson, M.: The Cog Project: Building a Humanoid Robot. In: Computation for Metaphors, Analogy, and Agents, pp 52–87. Springer-Verlag (1999)

  8. Burghart, C., Mikut, R., Stiefelhagen, R.: A cognitive architecture for a humanoid robot: a first approach. Humanoid Robots, 357–362 (2005)

  9. Calinon, S.: Robot programming by demonstration: a probabilistic approach. EPFL/CRC Press (2009)

  10. Chiaverini, S., Siciliano, B.: The unit quaternion: a useful tool for inverse kinematics of robot manipulators. Syst. Anal. Model. Simul. 35(1), 45–60 (1999)

    MATH  Google Scholar 

  11. Choi, D., Kang, Y., Lim, H.: Knowledge-based control of a humanoid robot. Intelligent Robots and, 3949–3954 (2009)

  12. Clark, A.: Mind and causality. Advances in Consciousness Research, chap. Embodiment and the Philosophy of Mind. John Benjamins Public (2004)

  13. Duch, W., Oentaryo, R.J., Pasquier, M.: Cognitive Architectures: Where Do We Go from Here?. In: Proceedings of the 2008 Conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference, pp 122–136. IOS Press, Amsterdam, The Netherlands (2008)

  14. Galindo, C., Gonzalez, J., Fernández-Madrigal, J.: An Architecture for Cognitive Human-Robot Integration. Application to Rehabilitation Robotics. In: 2005 IEEE International Conference Mechatronics and Automation, vol. 1, pp 329–334. IEEE (2005)

  15. García, D.H., Monje, C.A., Balaguer, C.: Adaptation of robot skills models to new task contraints. Int. J. Humanoid Robot. 12(3), 15500,241,155002,416 (2015). doi:10.1142/S0219843615500243

    Article  Google Scholar 

  16. Hernández García, D., Monje, C.A., Balaguer, C.: Framework for Learning and Adaptation of Humanoid Robot Skills to Task Constraints. In: Armada, M.A., Sanfeliu, A., Ferre, M. (eds.) ROBOT2013: First Iberian Robotics Conference, Advances in Intelligent Systems and Computing, vol. 252, pp 557–572. Springer International Publishing (2014)

  17. Hernández García, D., Monje, C.A., Balaguer, C.: Generation and Adaptation of Robot Skills Models. In: 2014 14Th IEEE-RAS International Conference On Humanoid Robots (Humanoids), pp 173–178 (2014)

  18. Hernández García, D., Monje, C.A., Balaguer, C.: Knowledge Base Representation for Humanoid Robot Skills. In: Proceedings of the 19Th IFAC World Congress, 2014, vol. 19, pp 3042–3047. International Federation of Automatic Control (2014)

  19. Ijspeert, A., Nakanishi, J., Schaal, S.: Trajectory formation for imitation with nonlinear dynamical systems. In: 2001 IEEE/RSJ International Conference on Proceedings Intelligent Robots and Systems. doi:10.1109/IROS.2001.976259, vol. 2, pp 752–757

  20. Jung, Y., Choi, Y., Park, H., Shin, W., Myaeng, S.H.: Integrating Robot Task Scripts with a Cognitive Architecture for Cognitive Human-Robot Interactions, 152–157 (2007). doi:10.1109/IRI.2007.4296613

  21. Kajita, S., Kanehiro, F., Kaneko, K., Yokoi, K., Hirukawa, H.: The 3D Linear Inverted Pendulum Mode: a Simple Modeling for a Biped Walking Pattern Generation. In: Proceedings of IEEE/RSJ International Conference On Intelligent Robots and Systems, vol. 1, pp 239–246 (2001)

  22. Khansari-Zadeh, S., Billard, A.: Imitation learning of globally stable non-linear point-to-point robot motions using nonlinear programming. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp 2676–2683 (2010). doi:10.1109/IROS.2010.5651259

  23. Khansari-Zadeh, S., Billard, A.: Learning stable nonlinear dynamical systems with gaussian mixture models. IEEE Trans. Robot. 27(5), 943 –957 (2011). doi:10.1109/TRO.2011.2159412

    Article  Google Scholar 

  24. Kieras, D.E., Meyer, D.E.: An overview of the epic architecture for cognition and performance with application to human-computer interaction. Hum.-Comput. Interact. 12(4), 391–438 (1997)

    Article  Google Scholar 

  25. Kim, K., Lee, J.Y., Choi, D., Park, J.M., You, B.J.: Autonomous task execution of a humanoid robot using a cognitive model. In: 2010 IEEE International Conference on Robotics and Biomimetics. doi:10.1109/ROBIO.2010.5723361, pp 405–410 (2010)

  26. Krüger, N., Piater, J., Wörgötter, F., Geib, C., Petrick, R., Steedman, M., Ude, A., Asfour, T., Kraft, D., Omrcen, D., Hommel, B., Agostino, A., Kragic, D., Eklundh, J., Krüger, V., Dillmann, R.: A Formal Definition of Object Action Complexes and Examples at Different Levels of the Process Hierarchy. Technical Report, EU project PACO-PLUS (2009)

  27. Laird, J.E., Newell, A., Rosenbloom, P.S.: Soar: an architecture for general intelligence. Artif. Intell. 33(1), 1–64 (1987)

    Article  Google Scholar 

  28. Langley, P., Laird, J.E., Rogers, S.: Cognitive architectures: Research issues and challenges. Cogn. Syst. Res. 10(2), 141–160 (2009). doi:10.1016/j.cogsys.2006.07.004

    Article  Google Scholar 

  29. Lemaignan, S., Ros, R., Mo senlechner, L., Alami, R., Beetz, M.: ORO, a knowledge management platform for cognitive architectures in robotics. In: 2010 IEEE/RSJ International Conference On Intelligent Robots and Systems (IROS), pp 3548–3553. IEEE (2010)

  30. Levesque, H., Lakemeyer, G.: Chapter 23 cognitive robotics. In: Frank van Harmelen, V.L., Porter, B. (eds.) Handbook of Knowledge Representation, vol. 6526, pp 869–886. Elsevier (2008). doi:10.1016/S1574-6526(07)03023-4

  31. Monje, C.A., Pierro, P., Balaguer, C.: Humanoid robot rh-1 for collaborative tasks: a control architecture for human-robot cooperation. Appl. Bionics Biomech. 5(4), 225–234 (2008)

    Article  Google Scholar 

  32. Pierro, P., Hernandez, D., Gonzalez-Fierro, M., Blasi, L., Milani, A., Balaguer, C.: Humanoid Teleoperation System for Space Environments. In: International Conference On Advanced Robotics, 2009. ICAR 2009, pp 1 –6 (2009)

  33. Poole, D., Mackworth, A., Goebel, R.: Computational intelligence: a logical approach. Oxford university Press, USA (1998)

    MATH  Google Scholar 

  34. Scassellati, B.: Theory of mind for a humanoid robot. Auton. Robot. 12(1), 13–24 (2002). doi:10.1023/A:1013298507114

    Article  MATH  Google Scholar 

  35. Schaal, S.: Is imitation learning the route to humanoid robots? Trends Cogn. Sci. 6, 233–242 (1999)

    Article  Google Scholar 

  36. Shanahan, M.: A cognitive architecture that combines internal simulation with a global workspace. Conscious. Cogn. 15, 433–449 (2006). doi:10.1016/j.concog.2005.11.005

    Article  Google Scholar 

  37. Siciliano, B., Sciavicco, L., Villani, L., Oriolo, G.: Robotics: Modelling, planning and control, 2nd edn. Advanced Textbooks in Control and Signal Processing. Springer (2009)

  38. Sun, R.: Multi-agent systems for society. chapter Cognitive Architectures and Multi-agent Social Simulation, p 7–21. Springer-Verlag, Berlin, Heidelberg (2009)

    Google Scholar 

  39. Tan, H.: The future of humanoid robots - research and applications, chapter Implementation of a Framework for Imitation Learning on a Humanoid Robot Using a Cognitive Architecture, pp 191–210. InTech (2012)

  40. Tenorth, M., Beetz, M.: Knowrob: a knowledge processing infrastructure for cognition-enabled robots. Int. J. Robot. Res. (IJRR) 32(5), 566–590 (2013)

    Article  Google Scholar 

  41. Vernon, D., Metta, G., Sandini, G.: A survey of artificial cognitive systems: Implications for the autonomous development of mental capabilities in computational agents. IEEE Trans. Evol. Comput. 11 (2), 151–180 (2007). doi:10.1109/TEVC.2006.890274

    Article  Google Scholar 

  42. Waibel, M., Beetz, M., Civera, J., D’Andrea, R., Elfring, J., Galvez-Lopez, D., Haussermann, K., Janssen, R., Montiel, J.M.M., Perzylo, A., Schiessle, B., Tenorth, M., Zweigle, O., Van de Molengraft, R.: Roboearth. IEEE Robot. Autom. Mag. 18(2), 69–82 (2011). doi:10.1109/MRA.2011.941632

    Article  Google Scholar 

  43. Zoliner, R., Pardowitz, M., Knoop, S., Dillmann, R.: Towards Cognitive Robots: Building Hierarchical Task Representations of Manipulations from Human Demonstration. In: Proceedings of the 2005 IEEE International Conference On Robotics and Automation, 2005. ICRA 2005, pp 1535–1540. IEEE (2005)

Download references

Author information

Authors and Affiliations

  1. University Carlos III of Madrid, Madrid, Spain

    Daniel Hernández García, Concepción A. Monje & Carlos Balaguer

Authors
  1. Daniel Hernández García
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Concepción A. Monje
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Carlos Balaguer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daniel Hernández García.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hernández García, D., Monje, C.A. & Balaguer, C. Task Oriented Control of a Humanoid Robot Through the Implementation of a Cognitive Architecture. J Intell Robot Syst 85, 3–25 (2017). https://doi.org/10.1007/s10846-016-0383-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-016-0383-7

Keywords

Search

Navigation